2026 Stablecoin Freezing Trends: Analysis of Patterns, Risks, and Compliance Strategies

Beosin

In recent years, the global regulatory landscape for anti-money laundering (AML) and counter-terrorism financing (CFT) in virtual assets has undergone profound changes. Regulatory authorities worldwide have significantly increased their focus on virtual assets, particularly stablecoins. The Financial Action Task Force (FATF)'s Special Report on Stablecoins and Unhosted Wallets, released in March 2026, explicitly states that stablecoins accounted for 84% of illegal virtual asset transaction volumes in 2025 and are widely used for money laundering, terrorist financing, and large-scale weapons proliferation financing.

Under this context, the concentrated freezing actions on TRON and ETH blockchains involving USDT and USDC between March and April 2026 serve as a critical window for observing the evolution of on-chain anti-money laundering practices. This paper, leveraging monitoring data from Beosin Stablecoin Monitor, analyzes the scale of freezes, on-chain fund linkages, and off-chain intelligence to accurately depict the status of stablecoin freezes, assess potential fund flow risks, and provide targeted blockchain-based anti-money laundering strategies.

According to monitoring data, between March and April 2026, the number of newly frozen addresses and the volume of funds on the TRON and Ethereum chains for USDT and USDC increased significantly. A total of 1,397 addresses were frozen, with direct frozen funds amounting to approximately $722 million, and the historical transaction volume of these frozen addresses exceeded $25 billion.

Looking at the distribution of daily frozen addresses, the number of frozen addresses increased after the start of the U.S.-Iran conflict, with a daily peak exceeding 600 addresses occurring after March 21.

Looking at the changes in the volume of frozen funds, the amount of frozen funds shows a stepwise upward trend, directly corresponding to the event in late April when Tether, in coordination with OFAC, froze $344 million in USDT related to the Central Bank of Iran. This indirectly indicates that on-chain freezes involve not only large-scale address blocking but also targeted actions against high-value fund pathways.

Additionally, on-chain freeze data from March to April 2026 reveals a clear temporal clustering pattern in stablecoin freezing activities, with USDC and USDT exhibiting significant temporal differentiation, reflecting distinct governance logic and user scenario differences between their respective issuers. The peak freezing periods also indirectly highlight varying regulatory responses by issuers toward specific regions.

USDT freezing activity shows several distinct peaks: 12:00–13:00, 16:00–17:00, and 21:00–22:00 (corresponding to 8:00 Dubai time, 9:00 UK time, and 9:00 Eastern Time in the US), while frequencies are lower from midnight to midday Beijing time, reflecting Tether’s responsiveness to law enforcement actions across multiple countries and its global risk management posture.

The freezing of USDC is highly concentrated at 4:00 AM Beijing Time (4:00 PM Eastern Time), with significantly fewer operations occurring at other times. This distribution aligns closely with its handling methodology and user scenarios: the primary users of USDC are institutions, and the processing of suspicious addresses is uniformly executed by the issuer, with bulk compliance, risk control, and address review activities concentrated during U.S. business hours.

Based on a comprehensive evaluation incorporating Beosin KYT’s over 5 billion address labels, on-chain transaction notes (Simplified Chinese), address-related sentiment, and Chinese-language tokens, the association between Chinese-speaking funds and frozen addresses can be categorized into the following three types:

• Directly linked addresses: Identified through on-chain label matching, freezing both the target address and its counterparty address, based on comprehensive criteria including association with Chinese-language black-market shops, underground banks, risk alerts related to criminal activity, and on-chain transfers containing Chinese text.
• Indirectly associated addresses: Determined by analyzing on-chain user behavior, such as transfers involving Chinese tokens, use of wallet applications commonly used by Chinese users, or direct financial transactions with platforms linked to Chinese entities;
• Suspected associated addresses: Determined comprehensively based on conditions such as suspected multiple CNY exchange transaction scenarios (identified by on-chain transaction data matching, where historical USDT and USDC transactions from frozen addresses include over 10 transactions with values in whole-number multiples of CNY) and indirect associations between counterparties.

Based on the newly frozen USDT and USDC addresses and related transaction data on the TRON and ETH chains from March to April 2026, we can observe the high-risk situation facing Chinese capital pathways:

1. Dimension of frozen address count: Among the sample data, 1,397 addresses were frozen. Of these, a total of 779 addresses potentially linked to Chinese funds (including direct, indirect, and suspected links) account for 56%, comprising 220 directly linked addresses (16%), 523 indirectly linked addresses (37%), and 36 suspected linked addresses (3%).

2. Frozen Funds by Scale: In the sample data, approximately $722 million in funds were frozen. Of this, about $135 million—19% of the total—may be directly, indirectly, or potentially linked to Chinese-related funds. Specifically, $33.32 million (5%) were directly linked, $97.41 million (13%) were indirectly linked, and $4.1 million (1%) were potentially linked.

3. Historical Transaction Volume Dimension: The total transaction volume of frozen addresses in the sample data exceeds $25.9 billion. Of this, approximately $23.6 billion in frozen addresses may be directly, indirectly, or suspiciously linked to Chinese funds, accounting for a high proportion of 91%. The historical transaction volume of frozen addresses directly linked amounts to approximately $6.216 billion, representing 24%; those indirectly linked total approximately $15.787 billion, or 60.6%; and those suspiciously linked amount to approximately $1.693 billion, or 6.5%.

We observe direct, indirect, or suspected associations with Chinese capital, exhibiting a pattern of “high address concentration, low fund proportion, and extremely high transaction volume.” This indicates that although the directly frozen amounts tied to these associated addresses are relatively limited, they serve as major nodes in fund flows, carrying substantial historical transaction volumes. The potential risks along these related fund pathways require close attention.

The above analysis of concentrated freezes on stablecoins provides a detailed overview of on-chain AML efforts in terms of the quantity, amount, and temporal distribution of freezes, highlighting the high-risk exposure of Chinese capital pathways within the blockchain ecosystem. Currently, blockchain compliance is advancing rapidly, placing higher demands on the risk management capabilities of virtual asset service providers. Relevant compliance teams should:

1. Build on-chain monitoring capabilities to detect newly frozen or soon-to-be-frozen high-risk addresses, along with associated address clusters and on-chain and off-chain activities of counterparties, and develop corresponding risk control measures and response strategies.

2. Build on-chain behavior analysis capabilities to identify potential anomalous activities, such as large transfers to entirely new addresses or fund dispersal across multiple addresses; ensure that the team’s primary wallet, business wallets, and other addresses remain unaffected, and implement real-time alerts for suspicious addresses.

3. Enhance risk control capabilities using professional blockchain anti-money laundering tools to address on-chain fund risk assessment, monitoring, and alerting. Beosin KYT accurately identifies high-risk entities and assigns risk scores to various addresses and transactions through a vast database of address labels, transaction pattern analysis, and cross-chain parsing capabilities.

Looking ahead, blockchain anti-money laundering technologies will continue to evolve, and collaboration between stablecoin issuers and law enforcement agencies will grow even closer. Beosin will continue to deepen its expertise in blockchain security and compliance technologies, expand its global partner ecosystem, and work collaboratively with regulatory and law enforcement bodies, industry organizations, and enterprises to build a secure, compliant, and efficient virtual asset ecosystem.